A survey and a new selection criterion for statistical home range estimation

The home range of a specific animal describes the geographic area where this individual spends most of the time while carrying out its usual activities (eating, resting, reproduction, ...). Although a well-established definition of this concept is lacking, there is a variety of home range estimators. The first objective of this work is to review and categorize the statistical methodologies proposed in the literature to approximate the home range of an animal, based on a sample of observed locations. The second aim is to address the open question of choosing the "best" home range from a collection of them based on the same sample. We introduce a numerical index, based on a penalization criterion, to rank the estimated home ranges. The key idea is to balance the excess area covered by the estimator (with respect to the original sample) and a shape descriptor measuring the over-adjustment of the home range to the data. To our knowledge, apart from computing the home range area, our ranking procedure is the first one which is both applicable to real data and to any type of home range estimator. Further, the optimization of the selection index provides in fact a way to select the smoothing parameter for the kernel home range estimator. For clarity of exposition, we have applied all the estimation procedures and our selection proposal to a set of real locations of a Mongolian wolf using R as the statistical software. As a byproduct, this review contains a thorough revision of the implementation of home range estimators in the R language.